JuziBot

什么是 JuziBot？

JuziBot provides an enterprise AI employee platform for roles such as sales and customer support. Its reusable software stack combines workflow orchestration, company knowledge, tool execution, and agent testing. A forward-deployed engineering team maps the business process and configures AI roles to work through existing systems and communication channels.

Organizations can start with one role and expand to more workflows. Deployment options include public cloud, private infrastructure, hybrid arrangements, and preinstalled appliances. Purchasing is organized around agreed business outputs and role-specific delivery.

JuziBot 能做什么？

Configurable AI workflows

Turn company processes, response boundaries, and knowledge into executable agent workflows. Industry templates and multi-agent orchestration provide reusable starting points.

Company knowledge and memory

Bring documents and business rules into a shared knowledge layer. Surface conflicting material for human decisions and include source and version references in answers.

Business-system execution

Connect CRM, ticketing, knowledge bases, and other business systems. The execution layer uses APIs where available or screen interaction for systems without interfaces.

Testing and release review

Generate test cases, run batch acceptance and regression checks, and compare staged releases. Deployment gates include human approval.

Decision records and improvement

Record the knowledge source, model, context, decision path, and version for review. Use conversation feedback, test results, and quality tickets to refine deployed workflows.

Deployment and model options

Choose public-cloud, private, hybrid, or appliance deployment. Configure supported models, including DeepSeek, Zhipu, and Qwen, according to the workflow.

使用场景

“Customer service from approved knowledge”

Configure answers from company policies and connect the agent to IM, website, or internal channels, with review and handover arrangements suited to the process.

“Sales follow-up workflows”

Map lead follow-up and customer conversations into workflows connected to business systems, then review performance against agreed business outputs.

“Connect existing operational systems”

Use API or interface-based execution to move work across systems, including older software without a connecting API.

“Expand an enterprise AI rollout”

Start with one role, validate its responses and execution, and reuse approved workflows and deployment infrastructure when adding further roles.

常见问题

How does an enterprise rollout start?

The forward-deployed team reviews your business process, operating procedures, knowledge, and goals, then configures and deploys a role into the selected systems. The software provides reusable workflows and testing tools; scope is defined for the organization’s process.

Which deployment options are offered?

Public cloud, private deployment, hybrid deployment, and preinstalled appliances are offered. In the described hybrid arrangement, models run in the customer’s private cloud while the console runs in public cloud.

What can it connect to?

The platform connects to IM channels and enterprise systems such as CRM, ticketing, order systems, and knowledge bases. Workflows can be published to websites, APIs, and internal systems.

Is it tied to one model?

Model configuration can use supported providers such as DeepSeek, Zhipu, Qwen, Wenxin, or GPT. Selection is made for the scenario rather than fixed to one model family.

How is the AI employee offering priced?

Engagements are organized around agreed business outputs and deployment scope. Sales roles already offer lead-based charging. Role-specific delivery and commercial terms are defined for the engagement.

快速信息

Product type

Enterprise AI employee platform

Inputs

Business processes, knowledge, operating rules, and connected systems

Deployment

Public cloud, private, hybrid, or appliance

Implementation

Forward-deployed engineering and configurable workflows

Quality controls

Tests, release approval, decision records, and feedback

Commercial model

Paid outcome-based engagements; lead charging for sales roles